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Enabling the discovery of Adaptive Learning Resources for mobile learner

Enabling the discovery of Adaptive Learning Resources for mobile learner
Enabling the discovery of Adaptive Learning Resources for mobile learner
The current advancements in mobile and communication technologies provide mobile users with unprecedented
possibilities to learn on the move. The diversity in the capabilities of mobile devices as well as needs of mobile
learners have, however, created many challenges for learning resource providers. To cope with these diversity problems, many content adaptation techniques have been proposed to adapt learning resources based on learner’s needs, preferences, device constraints and usage context. These techniques enable the creation of Adaptive Learning Resources to provide personalized versions of learning resources. The one issue that has not been addressed is the discovery of the potentially most useful version of a learning resource in the adaptive space created by different Adaptive Learning Resources provided by different content providers. Existing search techniques are good enough to discover only static content which has one single version unlike adaptive content. In this paper, we address this challenge by providing an Adaptive Learning Resource Meta-Model (ALRM) to enable mobile learners discover the right Adaptive Learning Resource among the many Adaptive Resources which has the Potential Most Relevant Version (PMRV). We have implemented this model in a prototype application using RDF and used SPARQL query for resource selection.
mobile learning, adaptive mobile learning, adaptive resource discovery
Jalal, Asim
07c8bd95-dfe5-45c0-9464-6fb1c9e91ad0
Gibbins, Nicholas
98efd447-4aa7-411c-86d1-955a612eceac
Millard, David
4f19bca5-80dc-4533-a101-89a5a0e3b372
Al-Hashimi, Bashir
0b29c671-a6d2-459c-af68-c4614dce3b5d
Jalal, Asim
07c8bd95-dfe5-45c0-9464-6fb1c9e91ad0
Gibbins, Nicholas
98efd447-4aa7-411c-86d1-955a612eceac
Millard, David
4f19bca5-80dc-4533-a101-89a5a0e3b372
Al-Hashimi, Bashir
0b29c671-a6d2-459c-af68-c4614dce3b5d

Jalal, Asim, Gibbins, Nicholas, Millard, David and Al-Hashimi, Bashir (2012) Enabling the discovery of Adaptive Learning Resources for mobile learner. 11th World Conference on Mobile and Contextual Learning (mLearn 2012), Finland. 16 - 18 Oct 2012. 6 pp .

Record type: Conference or Workshop Item (Paper)

Abstract

The current advancements in mobile and communication technologies provide mobile users with unprecedented
possibilities to learn on the move. The diversity in the capabilities of mobile devices as well as needs of mobile
learners have, however, created many challenges for learning resource providers. To cope with these diversity problems, many content adaptation techniques have been proposed to adapt learning resources based on learner’s needs, preferences, device constraints and usage context. These techniques enable the creation of Adaptive Learning Resources to provide personalized versions of learning resources. The one issue that has not been addressed is the discovery of the potentially most useful version of a learning resource in the adaptive space created by different Adaptive Learning Resources provided by different content providers. Existing search techniques are good enough to discover only static content which has one single version unlike adaptive content. In this paper, we address this challenge by providing an Adaptive Learning Resource Meta-Model (ALRM) to enable mobile learners discover the right Adaptive Learning Resource among the many Adaptive Resources which has the Potential Most Relevant Version (PMRV). We have implemented this model in a prototype application using RDF and used SPARQL query for resource selection.

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More information

e-pub ahead of print date: 16 October 2012
Venue - Dates: 11th World Conference on Mobile and Contextual Learning (mLearn 2012), Finland, 2012-10-16 - 2012-10-18
Keywords: mobile learning, adaptive mobile learning, adaptive resource discovery
Organisations: Web & Internet Science

Identifiers

Local EPrints ID: 354908
URI: https://eprints.soton.ac.uk/id/eprint/354908
PURE UUID: ad23c413-40f1-42c2-adcd-8f42fcaae828
ORCID for Nicholas Gibbins: ORCID iD orcid.org/0000-0002-6140-9956
ORCID for David Millard: ORCID iD orcid.org/0000-0002-7512-2710

Catalogue record

Date deposited: 29 Jul 2013 10:21
Last modified: 06 Jun 2018 12:56

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